Advanced driver assistance systems (ADAS) with increasing automation maturity and availability in urban contexts are entering the market.Meanwhile, the situational context has been identified to play a crucial role in system comprehension and usage, yet its subcomponents and their relation to system comprehension remain an open research question.To gain insights in the role of the situation complexity regarding subjective system comprehension and different methodological aspects, this study applies a mixed quantitative and qualitative approach, focusing on signaled intersections as an exemplary scenario.An on-road study with forty-six participants was conducted, involving six traffic light scenarios (all experienced twice).Results indicate that while comprehension was generally high, the situational context, including environmental and traffic-related factors, affected subjective system understanding.The proposed approach sheds light on the role of mixed methods in ADAS research, which may provide insights for system developers and suggestions for user training content.

Human factors in the context of advanced driver assistance systems (ADAS) are commonly investigated in driving simulators. However, the validity of this approach has not been sufficiently verified. This article compares human factors concerning a level 2 ADAS between real-world driving and two different simulators (simBIG vs. simSMALL) in a three-part user study (N = 93). The results show that usability and the mental model were valid in both simulators. Cognitive load, acceptance, and user experience were also valid, but only in simBIG, with some anecdotal support for the validity of simSMALL. Surprisingly, trust was higher in the simulators compared to real-world driving. Participants consistently took over control from the level 2 system at the same locations throughout simulated and real-world drives, and system usage increased over time in all three test environments. These findings indicate relative validity of the simulators. Further research is necessary to verify the transferability of the presented findings to other ADAS and simulators.

New Advanced Driver Assistance Systems (ADAS) are now available to support urban driving. To adequately use ADAS, especially in complex situations, drivers must comprehend them. An on-road study was conducted to investigate the mental model development while interacting with a state-of-the-art ADAS in both a rural (less complex) and an urban context (more complex). Forty-six participants experienced two rounds of each context. After each round, drivers rated their mental model, acceptance, and trust. Results indicate that for the rural context participants learned the system functionality in the first round without further improvement. In the urban context the mental model was generally less accurate, but improved in the second round. Trust increased from the first to the second rural round while acceptance did not show a significant change within the context. The results provide a first glimpse into the importance of evaluating different contexts and interaction scenarios for ADAS.